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NJIT Mathematical Biology Seminar

Tuesday, February 10, 2009, 4:00pm
Cullimore Hall 611
New Jersey Institute of Technology

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Fault Diagnosis Engineering of Digital Circuits Can Identify Vulnerable Molecules in Complex Cellular Networks

Ali Abdi

Department of Electrical and Computer Engineering, NJIT

System biology envisions that the application of complex system engineering approaches to cell signaling networks will lead to novel understandings and subsequently new treatments for complex disorders. In the area of circuit fault diagnosis engineering, there are a variety of methods to identify the defective or vulnerable components of complex digital electronic circuits. In biological systems, however, our knowledge is limited regarding the vulnerability of interconnected signaling pathways to the dysfunction of each specific molecule. We show that by developing proper biologically-driven digital vulnerability assessment methods, the vulnerability of complex signaling networks to the possible dysfunction of each molecule can be determined. To demonstrate the utility of the proposed approach, three well-characterized signaling networks will be analyzed: the somatic cellular networks that regulate the activity of caspase-3 or p53 genes, and the CNS network which leads to the activation or inhibition of CREB. In the talk it will be shown that there are highly significant differences among the vulnerability values of different molecules. Most of the highly vulnerable molecules we diagnosed are closely related, and are experimentally known to be the key regulators of these networks. Novel critical molecules will be presented as well. Overall, biologically relevant vulnerable molecules in complex cellular networks can be identified, by developing biologically-oriented fault diagnosis engineering techniques. This cross-disciplinary study helps to extend our understanding of biological systems, due to its capability of finding the key molecules that have causative effects in human diseases. Such molecules are promising targets for drug development.